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Comparison of multichannel signal deconvolution algorithms in airborne LiDAR bathymetry based on wavelet transform.
Yue Song1, Houpu Li2, Guojun Zhai3
1Department of Navigation Engineering, Naval University of Engineering, Wuhan, 430033, China. songyue199602@163.com.
Scientific Reports
|August 21, 2021
Summary
Wavelet denoising enhances airborne LiDAR bathymetry accuracy by improving waveform processing. Four deconvolution algorithms were tested, with Richardson-Lucy deconvolution showing the best detection rate and constrained least-squares filter deconvolution proving most robust.
Area of Science:
- Geomatics Engineering
- Optical Remote Sensing
- Hydrographic Surveying
Background:
- Airborne LiDAR bathymetry is cost-effective for shallow waters.
- Extracting accurate bathymetric data requires robust waveform processing.
- Existing algorithms struggle with environmental and channel variations.
Purpose of the Study:
- To evaluate the impact of wavelet denoising on airborne LiDAR bathymetry.
- To compare the performance of four deconvolution algorithms for waveform processing.
- To determine the most effective method for accurate shallow-water depth extraction.
Main Methods:
- Wavelet denoising applied to received LiDAR waveforms.
- Testing Richardson-Lucy deconvolution (RLD), blind deconvolution (BD), Wiener filter deconvolution (WFD), and constrained least-squares filter deconvolution (RFD).
- Evaluation using simulated and measured multichannel datasets.
Main Results:
- Wavelet denoising significantly improves bathymetric extraction accuracy.
- All tested algorithms performed better on the orthogonal polarization channel (PMT2) than the horizontal polarization channel (PMT1).
- RLD offered the highest signal detection rate; RFD was the most robust. BD showed low efficiency, and WFD struggled in depths over 25m.
Conclusions:
- Pre-processing LiDAR waveforms with wavelet denoising is crucial for accurate bathymetry.
- Algorithm performance varies by polarization channel and water depth.
- RFD and RLD are recommended for robust and accurate airborne LiDAR bathymetry in shallow waters.
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